CN117434522A - Calibration method and device for laser radar and positioning equipment and calibration equipment - Google Patents

Calibration method and device for laser radar and positioning equipment and calibration equipment Download PDF

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CN117434522A
CN117434522A CN202210832283.0A CN202210832283A CN117434522A CN 117434522 A CN117434522 A CN 117434522A CN 202210832283 A CN202210832283 A CN 202210832283A CN 117434522 A CN117434522 A CN 117434522A
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preset
point cloud
calibration
cloud data
coordinates
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肖振宇
罗哲
谭雯心
蒋强卫
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Changsha Intelligent Driving Research Institute Co Ltd
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Changsha Intelligent Driving Research Institute Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/497—Means for monitoring or calibrating
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
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    • G—PHYSICS
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/23—Testing, monitoring, correcting or calibrating of receiver elements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F17/10—Complex mathematical operations
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10028—Range image; Depth image; 3D point clouds
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    • G—PHYSICS
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Abstract

The application discloses a calibration method, a calibration device and calibration equipment for laser radar and positioning equipment. The calibration method of the laser radar and the positioning equipment comprises the following steps: acquiring first point cloud data of calibration equipment corresponding to each sampling time in N preset sampling times to obtain N first point cloud data; corresponding to each sampling time, acquiring position information of the calibration equipment in a positioning equipment coordinate system, and obtaining N pieces of position information; determining first coordinates of a preset reference point in a laser radar coordinate system from each first point cloud data according to a preset position relation between the preset reference point and the calibration equipment to obtain N first coordinates; presetting second coordinates of the reference points in a coordinate system of positioning equipment to obtain N second coordinates; and determining calibration information of the laser radar and the positioning equipment according to the N first coordinates and the N second coordinates. According to the embodiment of the application, the accuracy of obtaining the calibration information between the laser radar and the positioning equipment can be improved.

Description

Calibration method and device for laser radar and positioning equipment and calibration equipment
Technical Field
The application belongs to the field of laser radars, and particularly relates to a calibration method, a calibration device and calibration equipment for a laser radar and positioning equipment.
Background
The laser radar becomes an important sensor in the fields of unmanned vehicle obstacle detection and tracking, three-dimensional map construction and the like by means of high-precision and accurate depth information. The current multi-sensor fusion of vehicles is more data that is deeply coupled to the lidar and the locating device.
For example, when data acquired by the laser radar and the positioning device are fused, external parameter calibration needs to be performed between the laser radar and the positioning device, so that the data acquired by the laser radar and the positioning device can be converted into the same coordinate system, and therefore, accurate external parameter calibration is the basis of multi-sensor fusion. Because of the sparse characteristic of the laser radar data, the laser radar and other positioning equipment are easy to obtain inaccurate calibration information when performing external parameter calibration, and the calibration accuracy is poor.
Disclosure of Invention
The embodiment of the application provides a calibration method, a calibration device and calibration equipment for laser radar and positioning equipment, which can improve the accuracy of obtaining calibration information between the laser radar and the positioning equipment.
In a first aspect, an embodiment of the present application provides a calibration method for a laser radar and a positioning device, including:
acquiring first point cloud data of calibration equipment corresponding to each sampling time in N preset sampling times to obtain N first point cloud data, wherein the calibration equipment comprises preset reference points, and the first point cloud data is acquired by a laser radar;
Corresponding to each sampling time, acquiring position information of the calibration equipment in a positioning equipment coordinate system, and obtaining N pieces of position information;
determining first coordinates of a preset reference point in a laser radar coordinate system from each first point cloud data according to a preset position relation between the preset reference point and the calibration equipment to obtain N first coordinates; the method comprises the steps of,
determining second coordinates of a preset reference point in a positioning equipment coordinate system according to a preset position relation and each piece of position information to obtain N second coordinates;
and determining calibration information of the laser radar and the positioning equipment according to the N first coordinates and the N second coordinates.
In some implementations of the first aspect, obtaining the first point cloud data of the calibration device corresponding to each sampling time in N preset sampling times, to obtain N first point cloud data includes:
acquiring initial point cloud data of a target scene in N preset sampling times corresponding to each sampling time to obtain N initial point cloud data, wherein the target scene comprises calibration equipment;
generating a rotation matrix according to angle information between the normal direction of a preset plane in the initial point cloud data and the direction of a preset coordinate axis in a laser radar coordinate system according to each initial point cloud data;
According to the rotation matrix, carrying out rotation processing on each initial point cloud data to obtain N second point cloud data;
clustering is carried out on each second point cloud data to obtain a plurality of clustering clusters corresponding to each second point cloud data;
and screening the plurality of clusters according to the contour information of the calibration equipment corresponding to each second point cloud data to obtain first point cloud data of the calibration equipment.
In some implementations of the first aspect, a first preset position of the calibration device is provided with a calibration component with a preset spatial shape, the preset reference point is located at a second preset position of the calibration component, and according to a preset positional relationship between the preset reference point and the calibration device, first coordinates of the preset reference point in a laser radar coordinate system are determined from each first point cloud data, so as to obtain N first coordinates, including:
determining a first point cloud screening range according to the first preset position and the preset space shape of the calibration component;
according to the first point cloud screening range, fourth point cloud data corresponding to the calibration component are determined from each piece of first point cloud data, and N pieces of fourth point cloud data are obtained;
fitting each fourth point cloud data according to a space fitting function corresponding to a preset space shape, and determining N target point cloud data corresponding to the calibration part;
Determining a third coordinate of the preset reference point from each target point cloud data according to a second preset position of the preset reference point;
and determining a first coordinate of the preset reference point in a laser radar coordinate system according to the rotation matrix and the third coordinate.
In some implementations of the first aspect, fitting each fourth point cloud data according to a spatial fitting function corresponding to a preset spatial shape, to determine N target point cloud data corresponding to the calibration component includes:
fitting the fourth point cloud data according to a space fitting function corresponding to a preset space shape corresponding to each fourth point cloud data to obtain a first fitting equation corresponding to the calibration component;
judging whether the first fitting equation meets preset conditions or not;
when the first fitting equation meets the preset condition, determining target point cloud data corresponding to the calibration part from fourth point cloud data according to the first fitting equation;
and when the first fitting equation is not satisfied with the preset condition, continuing fitting processing on the fourth point cloud data according to the space fitting function corresponding to the preset space shape until a fitting equation meeting the preset condition is obtained.
In some implementations of the first aspect, the preset condition includes:
The fitting frequency is greater than the preset frequency;
or,
the number of points selected from the fourth point cloud data according to the first fitting equation is larger than the preset number, and the contour information corresponding to the first fitting equation is satisfied with a preset contour threshold range.
In some implementations of the first aspect, determining calibration information of the lidar and the positioning device according to the N first coordinates and the N second coordinates includes:
and according to the N first coordinates and the N second coordinates, resolving through a singular value decomposition algorithm to obtain calibration information of the laser radar and the positioning equipment.
In a second aspect, an embodiment of the present application provides a calibration device for a laser radar and a positioning device, where the device includes:
the acquisition module is used for acquiring first point cloud data of the calibration equipment corresponding to each sampling time in N preset sampling times to obtain N first point cloud data, wherein the calibration equipment comprises preset reference points, and the first point cloud data is acquired by the laser radar;
the acquisition module is also used for acquiring the position information of the calibration equipment in the coordinate system of the positioning equipment corresponding to each sampling time to obtain N pieces of position information;
the processing module is used for determining first coordinates of the preset reference point in a laser radar coordinate system from each first point cloud data according to the preset position relation between the preset reference point and the calibration equipment to obtain N first coordinates;
The processing module is further used for determining second coordinates of the preset reference point in a coordinate system of the positioning equipment according to the preset position relation and each piece of position information to obtain N second coordinates;
the processing module is also used for determining calibration information of the laser radar and the positioning equipment according to the N first coordinates and the N second coordinates.
In a third aspect, the present application provides a calibration device, which is applied to the calibration apparatus of the laser radar and positioning device described in the second aspect, where the calibration device includes a positioning apparatus and a calibration component with a preset spatial shape, and a preset position of the calibration component includes a preset reference point;
the positioning device is used for acquiring first position information, wherein the first position information is used for determining second position information of the calibration component and third position information of a preset reference point with a first preset position relation, and the first preset position relation is the position relation between the positioning device and the calibration component.
In a fourth aspect, the present application provides an electronic device, the device comprising: a processor and a memory storing computer program instructions; the processor executes computer program instructions to implement the method for calibrating a lidar and a positioning device described in the first aspect or any of the possible implementation manners of the first aspect.
In a fifth aspect, the present application provides a readable storage medium, on which computer program instructions are stored, which when executed by a processor implement a method for calibrating a lidar and a positioning device according to the first aspect or any of the realizations of the first aspect.
In a sixth aspect, embodiments of the present application provide a computer program product, where instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform a method for calibrating a lidar and a positioning device as described in the first aspect or any of the realizations of the first aspect.
The laser radar and positioning equipment calibrating method, device and equipment. And acquiring N first point cloud data acquired by the laser radar for the calibration equipment in N preset sampling times corresponding to each sampling time, and acquiring the position information of the calibration equipment in the coordinate system of the positioning equipment. Because the preset position of the calibration equipment comprises the preset reference point, according to the preset position relation between the preset reference point and the calibration equipment, the first coordinates of the preset reference point in the laser radar coordinate system can be determined from each first point cloud data, and N first coordinates are obtained; and determining second coordinates of the preset reference point in the coordinate system of the positioning equipment according to the preset position relation and each piece of position information to obtain N second coordinates, so that the position calculation accuracy of the preset reference point is improved, and finally, according to the N first coordinates and the N second coordinates, the calibration information of the laser radar and the positioning equipment can be accurately calculated.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described, and it is possible for a person skilled in the art to obtain other drawings according to these drawings without inventive effort.
FIG. 1 is a schematic structural diagram of a calibration system according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a calibration method of a laser radar and a positioning device according to an embodiment of the present application;
FIG. 3 is a schematic structural view of a calibration component according to an embodiment of the present application;
FIG. 4 is a schematic structural diagram of a calibration device for a laser radar and positioning apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Features and exemplary embodiments of various aspects of the present application are described in detail below to make the objects, technical solutions and advantages of the present application more apparent, and to further describe the present application in conjunction with the accompanying drawings and the detailed embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative of the application and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The laser radar becomes an important sensor in the fields of unmanned vehicle obstacle detection and tracking, three-dimensional map construction and the like by means of high-precision and accurate depth information. The current multi-sensor fusion of vehicles is more data that is deeply coupled to the lidar and the locating device.
For example, when data acquired by the laser radar and the positioning device are fused, external parameter calibration needs to be performed between the laser radar and the positioning device, so that the data acquired by the laser radar and the positioning device can be converted into the same coordinate system, and therefore, accurate external parameter calibration is the basis of multi-sensor fusion. Because of the sparse characteristic of the laser radar data, the laser radar and other positioning equipment are easy to obtain inaccurate calibration information when performing external parameter calibration, and the calibration accuracy is poor.
Aiming at the problem, the embodiment of the application provides a calibration method, a device and calibration equipment for laser radar and positioning equipment, which can improve the accuracy of obtaining calibration information between the laser radar and the positioning equipment.
The following describes a calibration method of a laser radar and positioning equipment provided by an embodiment of the application with reference to the accompanying drawings.
FIG. 1 is a schematic structural diagram of a calibration system according to an embodiment of the present application. Referring to FIG. 1, the calibration system includes a positioning device 110, a lidar 120, and a calibration device 130.
The positioning device 110 is an electronic device capable of acquiring position information and posture information of the positioning device 110 itself, for example, a combination navigation positioning device. The integrated navigational positioning device comprises a satellite positioning system and an inertial directional positioning navigational system (Integrated Positioning System, INS). The satellite positioning system may be a global positioning system (Global Positioning System, GPS), a beidou satellite navigation system or a global navigation satellite system (Global Navigation Satellite System, GNSS), which is not particularly limited herein.
The lidar 120 may be a mobile lidar or a non-repetitive lidar, and is not particularly limited herein.
In some embodiments of the present application, a calibration device is provided, the calibration device including a positioning device and a calibration component of a preset spatial shape, a preset position of the calibration component including a preset reference point; the positioning device is used for acquiring first position information, wherein the first position information is used for determining second position information of the calibration component and third position information of a preset reference point with a first preset position relation, and the first preset position relation is the position relation between the positioning device and the calibration component.
Illustratively, shown in connection with the marking device 130 of FIG. 1. The calibration device 130 comprises a positioning means 131 and a calibration member 132 of a preset spatial shape. Optionally, the calibration device 130 further comprises a fixed support member 133.
The positioning device 131 includes a satellite positioning system, which is used for acquiring position information of the calibration equipment. The satellite positioning system may be a global positioning system (Global Positioning System, GPS), a beidou satellite navigation system or a global navigation satellite system (Global Navigation Satellite System, GNSS), which is not particularly limited herein.
After the laser radar 120 scans the calibration device 130, the point cloud data corresponding to the calibration component 132 may be extracted according to a fitting function corresponding to the preset spatial shape. The first position information is used for determining the second position information of the calibration component 132 and the third position information of the preset reference point according to the first preset position relationship, and the first preset position relationship is the position relationship between the positioning device 131 and the calibration component 132.
The preset reference point may be located on the surface of the calibration component 132, or may be located inside the calibration component 132, which is not limited herein.
The positioning device 110 and the laser radar 120 are mounted on a movable carrier, and the calibration device 130 is located in a range of point cloud data which can be acquired by the laser radar 120. The movable carrier may be, for example, a vehicle, an unmanned aerial vehicle, or the like, and is not particularly limited herein. As shown in connection with fig. 1, the positioning device 110 and the lidar 120 are mounted above the vehicle. The data is acquired by the positioning device 110 and lidar 120 combination for use in constructing a three-dimensional map. To construct an accurate three-dimensional map for a particular application, external reference calibration of the positioning device 110 and the laser radar 120 is required. In the embodiment of the present application, the positioning device 110, the laser radar 120 and the calibration device 130 may be placed at an open position, and the positioning device 110 and the laser radar 120 may be calibrated by combining with the calibration device 130.
Fig. 2 is a flow chart illustrating a calibration method of a laser radar and a positioning device according to an embodiment of the present application. As shown in fig. 1, the method may include steps 210 through 250.
Step 210, acquiring first point cloud data of the calibration device corresponding to each sampling time in N preset sampling times, so as to obtain N first point cloud data.
The calibration device comprises a preset reference point, and the first point cloud data are acquired by a laser radar.
Step 220, corresponding to each sampling time, acquiring the position information of the calibration equipment in the coordinate system of the positioning equipment, and obtaining N pieces of position information.
Step 230, determining first coordinates of the preset reference point in the laser radar coordinate system from each first point cloud data according to the preset position relationship between the preset reference point and the calibration device, so as to obtain N first coordinates.
Step 240, determining second coordinates of the preset reference point in the coordinate system of the positioning device according to the preset position relation and each piece of position information, and obtaining N second coordinates.
And step 250, determining calibration information of the laser radar and the positioning equipment according to the N first coordinates and the N second coordinates.
According to the embodiment of the application, in N preset sampling times, corresponding to each sampling time, N first point cloud data acquired by a laser radar on calibration equipment are acquired, and position information of the calibration equipment in a coordinate system of the positioning equipment is acquired. Because the preset position of the calibration equipment comprises the preset reference point, according to the preset position relation between the preset reference point and the calibration equipment, the first coordinates of the preset reference point in the laser radar coordinate system can be determined from each first point cloud data, and N first coordinates are obtained; and determining second coordinates of the preset reference point in the coordinate system of the positioning equipment according to the preset position relation and each piece of position information to obtain N second coordinates, so that the position calculation accuracy of the preset reference point is improved, and finally, according to the N first coordinates and the N second coordinates, the calibration information of the laser radar and the positioning equipment can be accurately calculated.
Specifically, referring to step 210, n is a positive integer greater than 1, that is, a plurality of sampling times may be set in the embodiment of the present application. Illustratively, N may be 10.
And sampling data of the calibration equipment in each sampling time to obtain a group of data for calculating calibration information, wherein each group of data comprises a first coordinate of a preset reference point in a laser radar coordinate system and a second coordinate of the preset reference point in a positioning equipment coordinate system. By setting a plurality of sampling times, a plurality of sets of data for calculating calibration information can be obtained.
The calibration equipment is provided with a preset reference point, and the setting position of the preset reference point can be set according to the actual acquisition requirement. For example, the preset reference point may be positioned in the calibration device directly below the satellite positioning system for ease of calculation.
In some embodiments, a dense local map is constructed by scanning the calibration device with laser light, wherein the point cloud of the calibration device is enclosed in the local map. By extracting data from the local map, first point cloud data of the calibration device can be obtained.
As a specific example, the first point cloud data of the calibration device is acquired, which may specifically include steps 211 to 215.
Step 211, acquiring initial point cloud data of the target scene corresponding to each sampling time in the N preset sampling times, so as to obtain N initial point cloud data.
The target scene comprises calibration equipment.
Specifically, the target scene is a scene scanned by a laser radar. Alternatively, a relatively flat space may be selected in which the calibration device is placed, which is not particularly limited in this application. In each sampling time, scanning the target scene by the laser radar to obtain initial point cloud data of the target scene.
Wherein the initial point cloud data is a corresponding dense local map of the target scene. The dense local map can be obtained by scanning the target scene according to the laser radar. The lidar may be a repetitive lidar or a non-repetitive lidar, for example.
Taking the repetitive lidar as an example, the repetitive lidar may be mounted on a movable carrier, such as a vehicle. The repetitive lidar is mounted on a vehicle, and in the process that the vehicle moves along a predetermined track, the repetitive lidar is controlled to scan a target scene to obtain multiple frames of radar (lidar) data, and pose information, namely position information and pose information, of the non-repetitive lidar is recorded corresponding to each frame of lidar data.
Optionally, in the process that the vehicle moves 10 meters along the preset track, the repetitive lidar is controlled to acquire 100 frames of lidar data, and pose information of the repetitive lidar corresponding to each frame of lidar data. And matching and splicing 100 frames of lidar data according to pose information of the repeated lidar corresponding to each frame of lidar data to obtain a dense local map. For example, lidar odometry and real-time mapping (LOAM) algorithms may be employed by extracting feature information, such as planar features and local features, in each frame of lidar data. Optionally, the feature information of each frame is matched with the pose information of the first frame by an iterative nearest point algorithm (Iterative Closest Point, ICP), point-to-line matching is performed by using line features, and point-to-surface matching is performed by using surface features. And minimizing the matching error of the point-to-line characteristic and the point-to-surface characteristic, and calculating the relative pose between pose information corresponding to the lidar data of each frame and pose information corresponding to the first frame. And combining each relative pose, and superposing lidar data of each frame and the corresponding pose to obtain a dense local map, namely initial point cloud data.
In another specific example, taking a non-repetitive lidar as an example, the non-repetitive lidar is kept stationary, and the target scene is scanned for a preset period of time. And overlapping and splicing the multi-frame data acquired within the preset time length to obtain a dense local map, namely initial point cloud data.
According to the embodiment of the application, the laser data can completely cover the calibration equipment by constructing the dense local map, so that the calibration precision of the calibration information between the laser radar and the positioning equipment is improved.
Step 212, corresponding to each initial point cloud data, generating a rotation matrix according to angle information between a normal direction of a preset plane in the initial point cloud data and a preset coordinate axis direction in a laser radar coordinate system.
Step 213, performing rotation processing on each initial point cloud data according to the rotation matrix to obtain N second point cloud data;
for example, the preset plane in the initial point cloud data may be a ground plane. As a specific example, the preset flat surface may be obtained according to the following steps: after the initial point cloud data are obtained, carrying out plane fitting processing on the initial point cloud data, and determining a preset plane in each initial point cloud data, wherein the preset plane meets preset plane screening conditions. For example, by screening the conditions, it is possible to determine the ground plane as a preset plane from a plurality of fitting planes. The preset plane screening conditions may be set according to the actual target scene, and are not particularly limited herein.
For example, a random sample consensus (Random sample Consensus, ranac) algorithm may be used to perform a plane fitting process on the initial point cloud data to obtain a plurality of fitted planes. And acquiring a plane with the largest area from the plurality of fitting planes as a preset plane.
Specifically, the preset coordinate axis direction in the laser radar coordinate system may be a Z-axis direction. Calculating the included angle between the normal vector of the preset plane and the Z axis, and obtaining the pitch angle and the roll angle of the preset plane and the Z axis, wherein the two angles are included angle information of the laser radar and the preset plane. And constructing a rotation matrix R0 according to the pitch angle and the roll angle of the preset plane and the Z axis. Each initial point cloud data is rotated according to the rotation matrix R0, and for example, the initial point cloud data may be converted to a horizontal plane with a ground plane as a reference, to obtain second point cloud data.
According to the embodiment of the application, the initial point cloud data are converted to the preset plane, so that calculation errors caused by a certain included angle with the xoy plane due to the fact that the laser radar is possibly uneven in installation can be avoided.
After the second point cloud data is calculated, step 214 may be performed.
Step 214, clustering is performed on each second point cloud data to obtain a plurality of clusters corresponding to each second point cloud data.
Alternatively, when clustering is performed on each of the second point cloud data, an euro-type clustering algorithm or the like may be employed, which is not particularly limited herein.
Taking the preset plane as the ground plane as an example, in some embodiments, before the clustering processing is performed on the second point cloud data, the following steps may be further performed: corresponding to each second point cloud data, acquiring points with a first distance smaller than a first preset distance in the second point cloud data to obtain third point cloud data, wherein the first preset distance is determined according to the distance between the laser radar and the ground plane, and the first distance is the distance between the point and the horizontal plane where the laser radar is located; and clustering the third point cloud data to obtain a plurality of clustering clusters corresponding to the second point cloud data.
Specifically, the first preset distance may be a sum of a laser radar height and a preset adjustment parameter, where the first preset distance is (h0+h), where H0 is a height of the laser radar relative to the ground plane, and H is the first preset adjustment parameter. And the situation of false deletion is avoided by setting the adjustment parameters.
Since the second point cloud data has been converted to the preset plane. Taking the ground plane as an example, dividing two sides by the ground, wherein the point on one side above the ground plane of the laser radar and the point on the other side outside the ground plane do not necessarily comprise point cloud data corresponding to the calibration device. Therefore, only the points with the first distance smaller than the first preset distance in the second point cloud data can be acquired, and third point cloud data can be obtained. That is, points at a distance greater than (h0+h) from the plane in which the laser radar height lies are removed. The remaining points in the second point cloud data are third point cloud data.
In the subsequent clustering process, only the third point cloud data is required to be clustered, and a plurality of clustering clusters corresponding to each second point cloud data can be obtained. According to the embodiment of the application, the data processing amount can be effectively reduced and the data processing speed can be improved by extracting the data of the second point cloud data.
After obtaining a plurality of clusters corresponding to each second point cloud data, step 215 may be performed.
And step 215, screening the plurality of clusters according to the contour information of the calibration equipment corresponding to each second point cloud data to obtain first point cloud data of the calibration equipment.
The calibration device may be arranged to have a fixed profile shape. Alternatively, the profile information of the calibration device may include at least one of height information and maximum width information. Illustratively, as shown in fig. 3, the calibration device has a height information of H1 and a maximum width information of W1.
Taking height information as an example, the screening range is set to a length greater than (a×h1). The value of a can be set according to the profile information of the calibration device, and is not particularly limited herein. For example, a has a value of 0.6. Illustratively, a cluster corresponding to a length greater than (a×h1) is taken as the target cluster. The points in the target cluster form first point cloud data of the calibration equipment.
In some embodiments, referring to step 230, a preset reference point is set in the calibration device, where the setting position of the preset reference point may be set according to the actual acquisition requirement. Alternatively, the preset reference point may be positioned directly below the satellite positioning system in the calibration device. The position relation between the laser radar and the calibration equipment is combined, after a coordinate system is established based on the laser radar, a preset reference point can be conveniently and rapidly found from first point cloud data in the laser radar coordinate system, and the first coordinate of the preset reference point in the laser radar coordinate system is determined.
As a specific example, the first preset position of the calibration device is provided with a calibration member of a preset spatial shape, and the preset reference point is located at the second preset position of the calibration member. Specifically, steps 231 to 235 may be included, where a first coordinate of the preset reference point in the laser radar coordinate system is determined.
Step 231, determining a first point cloud screening range according to the first preset position and the preset space shape of the calibration component.
Illustratively, as shown in connection with FIG. 3, the height of the highest point of the calibration device from the ground plane is H1. Optionally, the highest non-discrete point is determined from the second point cloud data to be the highest point of the calibration device.
In an embodiment of the application, the first preset position of the calibration device is provided with a calibration part of a preset spatial shape. It is understood that the first point cloud screening range may be determined according to the preset spatial shape and the first preset position of the calibration component, which is not limited herein.
Taking the example that the calibration member is spherical, the diameter of the calibration member is L as shown in fig. 3. Correspondingly, the screening ranges (H1-H2 +a1) to (H1-H2-L-a 2) can be determined, wherein a1 is a first adjustment parameter, a2 is a second adjustment parameter, and the situation of false deletion can be avoided by setting the adjustment parameters.
Step 232, determining fourth point cloud data corresponding to the calibration component from each first point cloud data according to the first point cloud screening range, and obtaining N fourth point cloud data.
Specifically, for the point cloud data corresponding to each sampling time in the N sampling times, the first point cloud screening range may be determined according to the screening range determining method, so as to obtain N fourth point cloud data corresponding to the calibration component.
And 233, fitting the fourth point cloud data according to a space fitting function corresponding to the preset space shape, and determining N target point cloud data corresponding to the calibration component.
Specifically, a fitting equation can be obtained by fitting the fourth point cloud data according to the spatial fitting function each time. Taking a preset space shape as an example, 4 points can be randomly selected during fitting processing, and a spherical equation corresponding to the 4 points is obtained through calculation.
In the embodiment of the application, a plurality of fitting equations can be selected, and a final target fitting equation in each fourth point cloud data is determined.
And extracting point cloud corresponding to the target fitting equation from the fourth point data to obtain target point cloud data of the calibration part.
As a specific example, the target point cloud data may be determined according to steps 301 to 302.
Step 301, corresponding to each fourth point cloud data, performing fitting processing on the fourth point cloud data according to a spatial fitting function corresponding to a preset spatial shape, and obtaining a first fitting equation corresponding to the calibration component.
Illustratively, continuing to take the sphere as an example, the first fit equation is a sphere equation. The spherical equation is shown in formula (1).
(x-x 0 ) 2 +(y-y 0 ) 2 +(z-z 0 ) 2 ＝r 2 (1)
Where (x, y, z) is the point in the fourth point cloud data and r is the radius of the fitting equation.
Step 302, it is determined whether the first fitting equation satisfies a preset condition.
Exemplary, the preset conditions include: the number of fitting processes is greater than a preset number. Alternatively, the preset conditions are as follows: the number of points selected from the fourth point cloud data according to the first fitting equation is larger than the preset number, and the contour information corresponding to the first fitting equation is satisfied with a preset contour threshold range.
And step 303, determining target point cloud data corresponding to the calibration component from the fourth point cloud data according to the first fitting equation when the first fitting equation meets the preset condition.
And step 304, when the first fitting equation is not satisfied with the preset condition, continuing fitting processing on the fourth point cloud data according to the space fitting function corresponding to the preset space shape until a fitting equation meeting the preset condition is obtained.
Illustratively, continuing with the spherical example, profile information corresponding by spherical equations may be represented by radii. For example, the radius r of the spherical equation of the preset profile threshold range is greater than or equal to 1.2 times the actual radius of the calibration component. When the radius r of the spherical equation is greater than or equal to 1.2 times of the actual radius of the calibration component, the profile information corresponding to the first fitting equation can be considered to be satisfied with the preset profile threshold range.
In the embodiment of the application, due to the characteristic of self-dispersion of the point cloud data, the calibration part with the preset space shape is used, and particularly when the calibration part is spherical, a smooth plane is obtained by fitting based on a spherical equation, so that the influence of noise caused by the dispersion of the point cloud data can be effectively reduced, the accuracy of extracting the point cloud data corresponding to the calibration part can be effectively improved, and the calculation accuracy of solving the preset reference point is improved.
In some embodiments, a point cloud may be defined according to a spherical equation, and after the spherical equation is solved, the number of points in the spherical equation range is counted, where the number of points is greater than a preset number. And selecting the fitting equation according to the preset condition, and stopping fitting calculation when the target fitting equation is obtained.
It is to be understood that the preset space shape may be a three-dimensional shape such as an ellipsoid, a cylinder, a cone, etc., which is not particularly limited herein.
According to the embodiment of the application, the corresponding point cloud data of the calibration component is selected through the space fitting function corresponding to the preset space shape, so that the calculation accuracy can be effectively improved, and the calculation error is reduced.
In the embodiment of the present application, after determining N target point cloud data corresponding to the calibration component, step 234 may be performed next.
Step 234, determining the third coordinates of the preset reference point from each target point cloud data according to the second preset position of the preset reference point.
Specifically, the preset reference point is located at a second preset position of the calibration component. For example, the second preset position may be located on the surface of the calibration member or may be located inside the calibration member, which is not particularly limited herein.
Illustratively, continuing to take the sphere as an example, the second predetermined location may be a center of the sphere. According to the obtained spherical equation, the coordinates of the sphere center can be rapidly determined in the cloud data of the target point corresponding to the calibration part, and the coordinates of the sphere center are used as the third coordinates, so that the calculation process is simple. And when the calibration part is spherical, a smooth plane is obtained based on a spherical equation by means of easy fitting, so that the influence of noise caused by point cloud data dispersion can be effectively reduced, and the positioning accuracy of the preset reference point is improved.
Step 235, determining a first coordinate of the preset reference point in the laser radar coordinate system according to the rotation matrix and the third coordinate.
Since in the embodiment of the application, the first point cloud data can be converted to the horizontal plane taking the preset plane as the reference in the passing of the pair, the second point cloud data is obtained. To avoid calculation errors, the third coordinate needs to be multiplied by the inverse of the rotation matrix R0 to obtain a preset reference point, so that the position under the laser radar coordinate system can be obtained, that is, the first coordinate of the preset reference point in the laser radar coordinate system.
In some embodiments of the present application, it is also necessary to calculate the second coordinates of the preset reference point in the coordinate system of the positioning apparatus.
The above step 220 is involved, and the position information of the calibration device in the coordinate system of the positioning device is obtained corresponding to each sampling time. As a specific example, the self-positioning first satellite positioning information, as well as the self-attitude information, may be obtained by the integrated navigation positioning device. And arranging a device comprising a satellite positioning system in the calibration equipment, so that second satellite positioning information of the calibration equipment can be directly obtained. Therefore, according to the relation between the first satellite positioning information and the second positioning information, the position information of the calibration equipment in the coordinate system of the positioning equipment can be obtained. According to the embodiment of the application, a plurality of pieces of position information can be obtained corresponding to a plurality of sampling times.
In particular, the positioning device may specifically be a combined navigation positioning device. According to the first satellite positioning information of the positioning equipment and the gesture information of the positioning equipment, a coordinate system of the positioning equipment can be established. According to satellite positioning information of the calibration equipment, position information of the calibration equipment in a coordinate system of the positioning equipment can be determined, and meanwhile, a second coordinate of the preset reference point in the coordinate system of the positioning equipment can be determined by combining the preset position relation between the preset reference point and the calibration equipment.
In some embodiments, a first coordinate of the preset reference point in the lidar coordinate system and a second coordinate of the preset reference point in the pointing device coordinate system are obtained as a set of data during each sampling time. Multiple sets of data can be obtained corresponding to multiple sampling times. And resolving the plurality of groups of data to determine calibration information of the laser radar and the positioning equipment.
As a specific example, according to the N first coordinates and the N second coordinates, a singular value decomposition algorithm is used to calculate, so as to obtain calibration information of the laser radar and the positioning device.
Specifically, the calibration information of the laser radar and the positioning device can include rotation matrix information and translation matrix information between the laser radar and the positioning device. Illustratively, the rotation matrix information is denoted as R and the translation matrix information is denoted as T. A singular value decomposition (Singular Value Decomposition, SVD) algorithm may be used to solve for rotation matrix information R and translation matrix information T of the laser radar and positioning device.
Specifically, for example, the set of first coordinates in the lidar coordinate system is denoted as x= { X1, X2,.. the set of second coordinates in the positioning device coordinate system is denoted y= { Y1, Y2,... And calculating to obtain calibration information by minimizing the distance error between the point pairs. Wherein the first coordinate and the second coordinate at the same sampling time are a point pair. Illustratively, when using the SDV algorithm, an objective function can be constructed first, as shown in equation (2).
/>
Next, a homography matrix H is calculated, where the homography matrix H may be as shown in equation (3).
Wherein Pxi =xi-Cx, P yi ＝Y i -C y Cx is the average centroid coordinate of the set of first coordinates,C y mean centroid coordinates, which are a set of second coordinates, +.>
And obtaining rotation matrix information R and translation matrix information T by constructing a homography matrix H and carrying out SVD decomposition on the homography matrix H. Wherein t=c x -RC y 。
According to the embodiment of the application, in N preset sampling times, corresponding to each sampling time, N first point cloud data acquired by the laser radar on the calibration equipment are acquired, and position information of the calibration equipment in the coordinate system of the positioning equipment is acquired. Because the preset position of the calibration equipment comprises the preset reference point, according to the preset position relation between the preset reference point and the calibration equipment, the first coordinates of the preset reference point in the laser radar coordinate system can be determined from each first point cloud data, and N first coordinates are obtained; and determining second coordinates of the preset reference point in the coordinate system of the positioning equipment according to the preset position relation and each piece of position information to obtain N second coordinates, so that the position calculation accuracy of the preset reference point is improved, and finally, according to the N first coordinates and the N second coordinates, the calibration information of the laser radar and the positioning equipment can be accurately calculated.
Based on the same inventive concept, the present application also provides a calibration device 400 of the laser radar and the positioning device, which corresponds to the calibration method of the laser radar and the positioning device. This is described in detail with reference to fig. 4.
Fig. 4 is a schematic structural diagram of a calibration device of a laser radar and positioning apparatus according to an embodiment of the present application, as shown in fig. 4, the calibration device 400 of a laser radar and positioning apparatus may include: an acquisition module 410 and a processing module 420.
The acquiring module 410 is configured to acquire first point cloud data of calibration equipment corresponding to each of N preset sampling times, to obtain N first point cloud data, where the calibration equipment includes a preset reference point, and the first point cloud data is acquired by a laser radar;
the acquiring module 410 is further configured to acquire position information of the calibration device in a coordinate system of the positioning device corresponding to each sampling time, so as to obtain N position information;
the processing module 420 is configured to determine, according to a preset positional relationship between a preset reference point and the calibration device, first coordinates of the preset reference point in the laser radar coordinate system from each first point cloud data, and obtain N first coordinates;
the processing module 420 is further configured to determine second coordinates of the preset reference point in the coordinate system of the positioning device according to the preset position relationship and each piece of position information, so as to obtain N second coordinates;
The processing module 420 is further configured to determine calibration information of the laser radar and the positioning device according to the N first coordinates and the N second coordinates.
In some embodiments, the obtaining module 410 is further configured to obtain, for each of N preset sampling times, initial point cloud data of a target scene, to obtain N initial point cloud data, where the target scene includes a calibration device;
the processing module 420 is further configured to generate a rotation matrix according to angle information between a normal direction of a preset plane in the initial point cloud data and a preset coordinate axis direction in the laser radar coordinate system, corresponding to each initial point cloud data;
the processing module 420 is further configured to perform rotation processing on each initial point cloud data according to the rotation matrix, so as to obtain N second point cloud data;
the processing module 420 is further configured to perform clustering processing on each second point cloud data to obtain a plurality of clusters corresponding to each second point cloud data;
the processing module 420 is further configured to screen the plurality of clusters according to the profile information of the calibration device to obtain first point cloud data of the calibration device, where the first point cloud data corresponds to each second point cloud data.
In some embodiments, the first preset position of the calibration device is provided with a calibration component of a preset spatial shape, and the preset reference point is located at the second preset position of the calibration component;
The processing module 420 is further configured to determine a first point cloud screening range according to the first preset position and the preset spatial shape of the calibration component;
the processing module 420 is further configured to determine fourth point cloud data corresponding to the calibration component from each first point cloud data according to the first point cloud screening range, so as to obtain N fourth point cloud data;
the processing module 420 is further configured to perform fitting processing on each fourth point cloud data according to a spatial fitting function corresponding to a preset spatial shape, and determine N target point cloud data corresponding to the calibration component;
the processing module 420 is further configured to determine a third coordinate of the preset reference point from each target point cloud data according to a second preset position of the preset reference point;
the processing module 420 is further configured to determine a first coordinate of the preset reference point in the lidar coordinate system according to the rotation matrix and the third coordinate.
In some embodiments, the apparatus further comprises:
the processing module 420 is further configured to perform fitting processing on the fourth point cloud data according to a spatial fitting function corresponding to a preset spatial shape, so as to obtain a first fitting equation corresponding to the calibration component;
the judging module is used for judging whether the first fitting equation meets preset conditions or not;
The processing module 420 is further configured to determine target point cloud data corresponding to the calibration component from the fourth point cloud data according to the first fitting equation when the first fitting equation meets a preset condition;
and the processing module 420 is further configured to, when the first fitting equation does not meet the preset condition, continue fitting the fourth point cloud data according to the spatial fitting function corresponding to the preset spatial shape until a fitting equation meeting the preset condition is obtained.
In some embodiments, the preset conditions include: the fitting frequency is greater than the preset frequency;
or,
the number of points selected from the fourth point cloud data according to the first fitting equation is larger than the preset number, and the contour information corresponding to the first fitting equation is satisfied with a preset contour threshold range.
In some embodiments, the processing module 420 is further configured to obtain calibration information of the laser radar and the positioning device by performing a solution according to the N first coordinates and the N second coordinates through a singular value decomposition algorithm.
It may be appreciated that the calibration device 400 of the laser radar and the positioning device according to the embodiments of the present application may correspond to an execution body of the calibration method of the laser radar and the positioning device according to the embodiments of the present application, and specific details of operations and/or functions of each module/unit of the calibration device 400 of the laser radar and the positioning device may be referred to the description of corresponding parts in the calibration method of the laser radar and the positioning device according to the embodiments of the present application, which is not repeated herein for brevity.
According to the calibration device of the laser radar and the positioning equipment, in N preset sampling times, N first point cloud data acquired by the laser radar on the positioning equipment are acquired corresponding to each sampling time, and position information of the positioning equipment in a coordinate system of the positioning equipment is acquired. Because the preset position of the calibration equipment comprises the preset reference point, according to the preset position relation between the preset reference point and the calibration equipment, the first coordinates of the preset reference point in the laser radar coordinate system can be determined from each first point cloud data, and N first coordinates are obtained; and determining second coordinates of the preset reference point in the coordinate system of the positioning equipment according to the preset position relation and each piece of position information to obtain N second coordinates, so that the position calculation accuracy of the preset reference point is improved, and finally, according to the N first coordinates and the N second coordinates, the calibration information of the laser radar and the positioning equipment can be accurately calculated.
Fig. 5 shows a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 5, the device may include a processor 501 and a memory 502 storing computer program instructions.
In particular, the processor 501 may include a central processing unit (Central Processing Unit, CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured to implement one or more integrated circuits of embodiments of the present application.
Memory 502 may include mass storage for information or instructions. By way of example, and not limitation, memory 502 may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing. In one example, memory 502 may include removable or non-removable (or fixed) media, or memory 502 may be a non-volatile solid state memory. Memory 502 may be internal or external to the electronic device.
The memory may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to methods in accordance with aspects of the present disclosure.
The processor 501 reads and executes the computer program instructions stored in the memory 502 to implement the method described in the embodiment of the present application, and achieve the corresponding technical effects achieved by executing the method in the embodiment of the present application, which is not described herein for brevity.
In one example, the electronic device may also include a communication interface 503 and a bus 510. As shown in fig. 5, the processor 501, the memory 502, and the communication interface 503 are connected to each other by a bus 510 and perform communication with each other.
The communication interface 503 is mainly used to implement communication between each module, apparatus, unit and/or device in the embodiments of the present application.
Bus 510 includes hardware, software, or both that couple components of the online information-flow billing device to each other. By way of example, and not limitation, the buses may include an accelerated graphics port (Accelerated Graphics Port, AGP) or other graphics Bus, an enhanced industry standard architecture (Extended Industry Standard Architecture, EISA) Bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an industry standard architecture (Industry Standard Architecture, ISA) Bus, an infiniband interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a micro channel architecture (MCa) Bus, a Peripheral Component Interconnect (PCI) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a video electronics standards association local (VLB) Bus, or other suitable Bus, or a combination of two or more of the above. Bus 510 may include one or more buses, where appropriate. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.
The electronic equipment can execute the calibration method of the laser radar and the positioning equipment in the embodiment of the application, so that the corresponding technical effects of the calibration method of the laser radar and the positioning equipment described in the embodiment of the application are achieved.
In addition, in combination with the calibration method of the laser radar and the positioning device in the above embodiment, the embodiment of the application may provide a readable storage medium for implementation. The readable storage medium having stored thereon computer program instructions; the computer program instructions, when executed by the processor, implement a method for calibrating a lidar and a positioning device according to any of the embodiments described above. Examples of readable storage media may be non-transitory machine readable media such as electronic circuits, semiconductor Memory devices, read-Only Memory (ROM), floppy disks, compact discs (Compact Disc Read-Only Memory, CD-ROMs), optical discs, hard disks, and the like.
It should be clear that the present application is not limited to the particular arrangements and processes described above and illustrated in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps, after appreciating the spirit of the present application.
The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by a data signal carried in a carrier wave. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor Memory devices, read-Only Memory (ROM), flash Memory, erasable Read-Only Memory (Erasable Read Only Memory, EROM), floppy disks, compact discs (Compact Disc Read-Only Memory, CD-ROM), optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like. The code segments may be downloaded via computer networks such as the internet, intranets, etc.
It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be different from the order in the embodiments, or several steps may be performed simultaneously.
In addition, in combination with the calibration method, the calibration device and the readable storage medium of the laser radar and the positioning device in the above embodiments, the embodiments of the present application may be implemented by providing a computer program product. Instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the method of calibrating a lidar and a positioning device according to any of the embodiments described above.
Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In the foregoing, only the specific embodiments of the present application are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, which are intended to be included in the scope of the present application.

Claims (11)

1. The method for calibrating the laser radar and the positioning equipment is characterized by comprising the following steps of:
acquiring first point cloud data of calibration equipment corresponding to each sampling time in N preset sampling times to obtain N first point cloud data, wherein the calibration equipment comprises preset reference points, and the first point cloud data is acquired by a laser radar;
acquiring the position information of the calibration equipment in the positioning equipment coordinate system corresponding to each sampling time to obtain N pieces of position information;
determining first coordinates of the preset reference point in the laser radar coordinate system from each first point cloud data according to the preset position relation between the preset reference point and the calibration equipment to obtain N first coordinates; the method comprises the steps of,
Determining second coordinates of the preset reference point in the positioning equipment coordinate system according to the preset position relation and each piece of position information to obtain N second coordinates;
and determining calibration information of the laser radar and the positioning equipment according to the N first coordinates and the N second coordinates.
2. The method of claim 1, wherein the obtaining the first point cloud data of the calibration device for each of the N preset sampling times to obtain N first point cloud data includes:
acquiring initial point cloud data of the target scene in the N preset sampling times, corresponding to each sampling time, to obtain N initial point cloud data, wherein the target scene comprises the calibration equipment;
generating a rotation matrix according to angle information between the normal direction of a preset plane in the initial point cloud data and the direction of a preset coordinate axis in a laser radar coordinate system corresponding to each initial point cloud data;
performing rotation processing on each initial point cloud data according to the rotation matrix to obtain N second point cloud data;
clustering processing is carried out on each second point cloud data to obtain a plurality of clustering clusters corresponding to each second point cloud data;
And screening the clustering clusters according to the profile information of the calibration equipment to obtain first point cloud data of the calibration equipment, wherein the second point cloud data correspond to the first point cloud data.
3. The method according to claim 2, wherein a first preset position of the calibration device is provided with a calibration component of a preset spatial shape, the preset reference point is located at a second preset position of the calibration component, and determining, from each of the first point cloud data, first coordinates of the preset reference point in the lidar coordinate system according to a preset positional relationship between the preset reference point and the calibration device, and obtaining N first coordinates includes:
determining a first point cloud screening range according to the first preset position and the preset space shape of the calibration component;
determining fourth point cloud data corresponding to the calibration component from each piece of first point cloud data according to the first point cloud screening range to obtain N pieces of fourth point cloud data;
fitting each fourth point cloud data according to a space fitting function corresponding to the preset space shape, and determining N target point cloud data corresponding to the calibration part;
Determining a third coordinate of the preset reference point from each target point cloud data according to a second preset position of the preset reference point;
and determining a first coordinate of the preset reference point in the laser radar coordinate system according to the rotation matrix and the third coordinate.
4. A method according to claim 3, wherein said fitting each of the fourth point cloud data according to the spatial fitting function corresponding to the preset spatial shape, and determining N target point cloud data corresponding to the calibration component, includes:
fitting the fourth point cloud data according to the space fitting function corresponding to the preset space shape corresponding to each fourth point cloud data to obtain a first fitting equation corresponding to the calibration component;
judging whether the first fitting equation meets a preset condition or not;
when the first fitting equation meets the preset condition, determining target point cloud data corresponding to the calibration part from the fourth point cloud data according to the first fitting equation;
and when the first fitting equation is not satisfied with a preset condition, continuing fitting processing on the fourth point cloud data according to the space fitting function corresponding to the preset space shape until a fitting equation meeting the preset condition is obtained.
5. The method of claim 6, wherein the preset conditions include:
the fitting frequency is greater than the preset frequency;
or,
and the number of points selected from the fourth point cloud data according to the first fitting equation is larger than a preset number, and the contour information corresponding to the first fitting equation is satisfied with a preset contour threshold range.
6. The method of claim 1, wherein determining calibration information for the lidar and the positioning device based on the N first coordinates and the N second coordinates comprises:
and according to the N first coordinates and the N second coordinates, resolving through a singular value decomposition algorithm to obtain calibration information of the laser radar and the positioning equipment.
7. A calibration device for a laser radar and positioning apparatus, the device comprising:
the acquisition module is used for acquiring first point cloud data of calibration equipment corresponding to each sampling time in N preset sampling times to obtain N first point cloud data, wherein the calibration equipment comprises preset reference points, and the first point cloud data is acquired by a laser radar;
The acquisition module is further used for acquiring the position information of the calibration equipment in the coordinate system of the positioning equipment corresponding to each sampling time to obtain N pieces of position information;
the processing module is used for determining first coordinates of the preset reference point in the laser radar coordinate system from each piece of first point cloud data according to the preset position relation between the preset reference point and the calibration equipment to obtain N first coordinates;
the processing module is further used for determining second coordinates of the preset reference point in the coordinate system of the positioning device according to the preset position relation and each piece of position information to obtain N second coordinates;
the processing module is further used for determining calibration information of the laser radar and the positioning equipment according to the N first coordinates and the N second coordinates.
8. A calibration device, characterized in that it is applied to the calibration apparatus of the laser radar and positioning device according to claim 9, comprising a positioning apparatus and a calibration member of a preset spatial shape, the preset position of the calibration member comprising a preset reference point;
the positioning device is used for acquiring first position information, wherein the first position information is used for determining second position information of the calibration component and third position information of the preset reference point with a first preset position relation, and the first preset position relation is the position relation between the positioning device and the calibration component.
9. An electronic device, the device comprising: a processor and a memory storing computer program instructions;
the processor reads and executes the computer program instructions to implement a method of calibrating a lidar and positioning device according to any of claims 1 to 6.
10. A readable storage medium, characterized in that it has stored thereon computer program instructions which, when executed by a processor, implement a method for calibrating a lidar and a positioning device according to any of claims 1 to 6.
11. A computer program product, characterized in that instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the method of calibrating a lidar and a positioning device according to any of claims 1-6.
CN202210832283.0A 2022-07-15 2022-07-15 Calibration method and device for laser radar and positioning equipment and calibration equipment Pending CN117434522A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117928680A (en) * 2024-03-21 2024-04-26 青岛清万水技术有限公司 Automatic positioning method and system for transducer, electronic equipment and storage medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117928680A (en) * 2024-03-21 2024-04-26 青岛清万水技术有限公司 Automatic positioning method and system for transducer, electronic equipment and storage medium
CN117928680B (en) * 2024-03-21 2024-06-07 青岛清万水技术有限公司 Automatic positioning method and system for transducer, electronic equipment and storage medium

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